What Data Analytics Actually Means, and Where It Fits at Work
A working definition of data analytics, why it matters, and how it's different from BI, data science, and data engineering, without the textbook language.
Practical guides on data analytics, business intelligence, data engineering, data science, and how AI is changing each discipline. Written for professionals, leaders, and anyone trying to understand how modern data teams actually work.
Read the Insights →A lot of the confusion around data careers and data teams comes from treating data engineering, data analytics, business intelligence, and data science as one blurry job. They work together, but each exists for a different purpose, serves different stakeholders, and answers different business questions.
Builds and maintains the pipelines, warehouses, and data models everything else depends on.
Standardises the numbers everyone agrees on, and reports them reliably, on a schedule.
Investigates why something happened and what's likely to happen, using BI's numbers as a starting point.
Turns patterns into models and products: forecasts, recommendations, automated decisions.
A working definition of data analytics, why it matters, and how it's different from BI, data science, and data engineering, without the textbook language.
A layer-by-layer look at what AI has genuinely taken off data teams' plates so far, and where it still gets things confidently wrong.